Co-estimation of state-of-charge and state-of-temperature for large-format lithium-ion batteries based on a novel electrothermal model

• DOI: 10.1016/j.geits.2024.100152
• Publication Date: 2024-01-06T17:08:05Z
• Authors: Chao Yu; Jiangong Zhu; Wenxue Liu; Haifeng Dai; Xuezhe Wei
• Keywords: State of charge

The safe and efficient operation of the electric vehicle significantly depends on accurate state-of-charge (SOC) state-of-temperature (SOT) Lithium-ion (Li-ion) batteries. Given influence cross-interference between two states indicated above, this study establishs a co-estimation framework battery SOC SOT. This framwork is based an innovative electrothermal model adaptive estimation algorithms. first-order RC thermal are components model. Specifically, includes lumped-mass submodels for tabs two-dimensional (2-D) resistance network (TRN) submodel main body, capable capturing detailed thermodynamics large-format Li-ion Moreover, proposed strikes acceptable compromise fidelity computational complexity by representing heat transfer processes resistances. Besides, algorithms composed unscented Kalman filter (AUKF) (AKF), which adaptively update state noise covariances. Regarding results, mean absolute errors (MAEs) SOT controlled within 1% 0.4 °C at temperatures, indicating that method yields superior prediction performance in wide temperature range 5 to 35 °C.